sign in sign up
<<
Home , Inhibitory control

The Shape of the ACC Contributes to Cognitive Control Efficiency in Preschoolers

Arnaud Cachia1,2*, Grégoire Borst1,2*, Julie Vidal1,2, Clara Fischer3, Arlette Pineau4, Jean-François Mangin3, and Olivier Houdé1,2,5 Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021

Abstract ■ Cognitive success at school and later in life is supported by lower Stroop interference scores for both RTs and error rates, including cognitive control (CC). The pFC in children with asymmetrical ACC sulcal pattern (i.e., different plays a major role in CC, particularly the dorsal part of ACC or pattern in each hemisphere) compared with children with sym- midcingulate cortex. Genes, environment (including school cur- metrical pattern (i.e., same pattern in both hemispheres). Criti- ricula), and neuroplasticity affect CC. However, no study to date cally, ACC sulcal pattern had no effect on performance in the has investigated whether ACC sulcal pattern, a stable feature forward and backward digit span tasks suggesting that ACC sulcal primarily determined in utero, influences CC efficiency in the pattern contributes to the executive ability to resolve conflicts early stages of cognitive and neural development. Using anatom- but not to the ability to maintain and manipulate information in ical MRI and three-dimensional reconstruction of cortical folds, working . This finding provides the first evidence that we investigated the effect that ACC sulcal pattern may have on preschoolersʼ CC efficiency is likely associated with ACC sulcal the Stroop score, a classical behavioral index of CC efficiency, in pattern, thereby suggesting that the brain shape could result in 5-year-old preschoolers. We found higher CC efficiency, that is, early constraints on human executive ability. ■

INTRODUCTION conflict condition, typically results in increased RTs and Cognitive control (CC) including inhibitory control—that error rates (ERs) because of the need to inhibit irrelevant is, the ability to overcome conflicts and inhibit a dominant stimulus feature (i.e., the color denoted by the word) to response—is one of the core executive functions that focus on an alternative feature of the stimulus (i.e., the enable us to resist habits or automatisms, temptations, ink color). The Stroop interference score reflect the ability distractions, or interference and allow us to adapt to of CC to overcome perceptual and cognitive conflicts complex situations by means of mental flexibility, namely, through the inhibition of a dominant response, namely dynamic inhibition/activation of competing cognitive reading when verbal material is presented (MacLeod, strategies (Diamond, 2013). The Stroop Color–Word task 1991). However, the Stroop Color–Word task involves (Stroop, 1935) is a seminal task designed to assess the other cognitive processes, such as selective , con- ability to process conflicting information, drawing, in part, flict monitoring, perceptual, semantic interference, re- on CC. In the classical Stroop Color–Word task, par- sponse interference, and working memory (MacLeod, ticipants are instructed to name the color of the ink of Dodd, Sheard, Wilson, & Bibi, 2003). Functional brain- printed words that denote colors. In the no-conflict con- imaging studies (Roberts & Hall, 2008; Matthews, Paulus, dition, the ink colors match the colors denoted by the Simmons, Nelesen, & Dimsdale, 2004; Bush, Luu, & words (e.g., “RED” appears in red ink), whereas in the Posner, 2000; Casey et al., 2000; Pardo, Pardo, Janer, & conflict condition, the colors denoted by the words inter- Raichle, 1990) have demonstrated that the medial pFC fere with the ink colors to be named (e.g., “RED” appears and more precisely the dorsal ACC, also referred to as the in blue ink). The conflict condition, in contrast to the no- midcingulate cortex (Vogt, 2009), is consistently activated in Stroop tasks (Petersen & Posner, 2012) and other tasks that involve overriding prepotent responses, selecting re- sponses in underdetermined contexts, or errors (Petersen 1CNRS U3521, Laboratory for the of Child Devel- & Posner, 2012). According to the conflict-monitoring opment and Education, Sorbonne, Paris, France, 2Université Paris Descartes, Paris, France, 3Computer-Assisted Neuroimaging hypothesis (Botvinick, 2007; Botvinick, Braver, Barch, Laboratory, Neurospin, I2BM, CEA, Gif/Yvette, France, 4Université Carter, & Cohen, 2001), one of the core functions of the Caen Basse Normandie, Caen, France, 5Institut Universitaire de dorsal ACC is to signal conflict in information processing France, Paris, France to the CC system supported through dorsolateral prefrontal *These authors contributed equally to this work. cortices. To resolve this conflict, the CC system increases

© 2013 Massachusetts Institute of Technology Journal of 26:1, pp. 96–106 doi:10.1162/jocn_a_00459 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021 the activation of task-relevant information and inhibits Guerrini, Kuzniecky, Jackson, & Dobyns, 2012; Rakic, task-irrelevant information (see Egner & Hirsch, 2005). 2004; Molko et al., 2003; Dehay, Giroud, Berland, Killackey, From a perspective, ex- & Kennedy, 1996). As opposed to quantitative measures ecutive functions including CC are known to support of the cortex morphology, such as the Gyrification Index qualities such as self-control, creativity, and reasoning (Zilles, Palomero-Gallagher, & Amunts, 2013; White, Su, that children require to be successful in school and later Schmidt, Kao, & Sapiro, 2010; Armstrong, Schleicher, in life (Diamond, 2013). Executive function efficiency is a Omran, Curtis, & Zilles, 1995) or cortex structure, such better predictor of school readiness and future academic as the thickness, surface, and volume (Giedd et al., 2009; success than intelligence quotient (Blair & Razza, 2007; Gogtay et al., 2004), that vary from childhood through Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021 Duckworth & Seligman, 2005). Given the critical role early adulthood, the sulcal pattern, a qualitative measure that executive functions play in academic achievement, of the cortex morphology, is a stable feature of the brain numerous studies have focused on how to improve anatomy apparently less affected by brain maturation, executive function efficiency. Diverse activities seem training, and occurring after birth (Sun et al., to increase executive function efficiency (Diamond & 2012). Two types of ACC sulcal pattern (Ono, Kubik, & Lee, 2011), including school curricula (Diamond, Barnett, Abarnathey, 1990) are defined between 10 and 15 weeks Thomas, & Munro, 2007), attention training (Rueda, of fetal life (White et al., 2010): the “single” type, with Rothbart, McCandliss, Saccomanno, & Posner, 2005), only the cingulate sulcus, and the “double parallel” type, computerized training (Holmes, Gathercole, & Dunning, with an additional paracingulate sulcus (PCS; Paus et al., 2009), noncomputerized games (Mackey, Hill, Stone, & 1996). Recent functional data indicate that participants Bunge, 2011), aerobics (Hillman, Erickson, & Kramer, without a PCS do not lack a particular cortical area, that 2008), martial arts (Lakes & Hoyt, 2004), yoga, and mindful- is, “single” and `“double parallel” ACC types are homolo- ness (Flook et al., 2010). For instance, Tools of the Mind— gous cortical regions (Amiez et al., 2013). The “double a school curriculum for preschool kindergarten that empha- parallel” is observed in 30–60% of individuals, and this sizes imaginary play—improves executive functions to a ACC type is more frequent in the left hemisphere (Yucel larger extent than high-quality school curricula based on et al., 2001). In adults, asymmetry in the sulcal pattern of literacy and thematic units (Diamond et al., 2007). ACC (i.e., the “single” type in the left hemisphere and From a neuroscience perspective, studies have demon- the “double parallel” type in the right hemisphere or vice strated that prolonged learning and specific trainings— versa) is associated with increased CC efficiency (Huster, leading to the improvement of cognitive efficiency—can Westerhausen, & Herrmann, 2011; Fornito et al., 2004) modify the structure (e.g., gray matter volume, cortical and the increased efficiency to manage cognitive conflicts thickness) of brain areas functionally related to the pro- and inhibit dominant responses as measured by the per- cesses trained (Hyde et al., 2009; Draganski et al., 2004, formance in a Stroop Color–Word task at the behavioral 2006). For example, adults who learned to juggle over and electrophysiological level (Huster, Enriquez-Geppert, a 3-month period present an increase of the gray matter Pantev, & Bruchmann, 2012; Huster et al., 2009). However, volume in the visual motion area. The increase of the gray no study to date has investigated whether the sulcal matter volume reveals one of the neuroplasticity mecha- pattern of ACC already affects CC efficiency in the early nisms mediating the improvement of cognitive ability stages of cognitive and neural development. following intense training (Draganski et al., 2004). This is In our study, using anatomical MRI, we investigated not limited to the motor domain; studies have demon- whether an early neurodevelopmental constraint—that strated variation of the structure of the brain in response is, the sulcal pattern of ACC—contributes to preschoolersʼ to intense learning for medical examinations (Draganski CC efficiency as measured by their performance on et al., 2006) and in response to 15 months of musical train- the “Animal Stroop task” (Wright, Waterman, Prescott, ing in early childhood—with a correlation between the & Murdoch-Eaton, 2003)—an adaptation of the Stroop structural brain changes induced by training and behav- Color–Word task for young nonreading children. In the ioral improvements (Hyde et al., 2009). Although there “Animal Stroop task” (Figure 1), children are required to is no study to date that has investigated the structural name an animalʼs body in a no-conflict condition—that change in ACC in response to CC training, previous studies is, the head and the animalʼs body are matched (e.g., have provided evidence that interindividual differences a duckʼs head on a duckʼs body)—and in a conflict con- in adultsʼ CC efficiency are associated with differences dition—that is, the head of the animal is replaced by the in the structure of ACC, that is, the local cortical thickness head of a different animal (e.g., a pigʼs head on a duckʼs (Westlye, Grydeland, Walhovd, & Fjell, 2011) or the local body). As in the classical Stroop Color–Word task, CC gray matter volume (Takeuchi et al., 2012) of ACC. efficiency is reflected by the difference in RTs (or ERs) Early determined anatomical features of ACC also con- between the conflict and the no-conflict conditions. tribute to interindividual differences in adultsʼ CC efficiency. If the sulcal pattern of ACC contributes to preschoolersʼ The sulcal pattern constitutes one of these early anatomi- CC efficiency, we expect lower Stroop interference cal factors (Welker, 1988). This pattern is determined scores (i.e., better CC efficiency) for children with asym- in utero by genetic and environmental factors (Barkovich, metric (i.e., the “single” type in the left hemisphere and

Cachia et al. 97 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021 Figure 1. Assessment of CC efficiency using the “Animal Stroop task.” (Left) A child performing the “Animal Stroop task” in the classroom. (Right) Example of “conflict” and “no-conflict” stimuli used in the “Animal Stroop task” to assess the CC efficiency of

preschoolers. Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021

the “double parallel” type in the right hemisphere or load (Gathercole, Pickering, Ambridge, & Wearing, 2004; vice versa) rather than symmetric (i.e., the “single” type Baddeley, 2003). or “double parallel” type in both hemispheres) sulcal pattern of ACC (Figure 2). In addition, to assess the specificity of the effect of METHODS ACC sulcal pattern on the CC efficiency of preschoolers, Participants the same group of children performed both forward and Nineteen 5-year-old right-handed preschoolers (mean ± backward digit span tasks from the Wechsler Intelligence standard deviation age: 5.47 ± 0.18 years; 11 girls) were Scale for Children (WISC-IV; see Wechsler, 2003). We recruited from a public preschool in Caen (France). reasoned that if ACC sulcal pattern contributes specifi- They had no history of neurological disease and no cally to the CC efficiency and not to the efficiency of cerebral abnormalities. The children were tested in ac- other executive functions, such as verbal working mem- cordance with national and international norms that ory, then ACC sulcal pattern should have no effect on the govern the use of human research participants. We ob- performance in the two-digit span tasks, even on the tained written informed consent from the childrenʼs backward digit span task, which requires more executive parents that allowed us to enroll their children in the study. The ethics committee approved our study (CPP Nord-Ouest III, France).

Behavioral Assessment The preschoolersʼ CC efficiency was assessed using the “Animal Stroop task,” an adaptation of the Stroop Color– Word task for preschoolers (Wright et al., 2003). Each preschooler performed two experimental conditions— each comprised 24 Animal Stroop stimuli printed on a sheet of paper. The stimuli were designed and based on four images of animals: a cow, a duck, a pig, and a sheep. In both conditions, the children were asked to name the animalʼs body. In the conflict condition, the head of the animal was substituted with the head of another animal. In the no-conflict condition, the head and the animalʼs body were matched (Figure 1). All preschoolers named each of the 24 animal bodies under the no-conflict con- dition before naming the 24 animal bodies under the con- flict condition. RTs and ERs were recorded separately for the conflict and the no-conflict conditions. The Stroop interference score was defined as the differences in RTs or ERs between the two experimental conditions. The higher Stroop interference scores reflected lower CC efficiency in these children. The verbal working memory efficiency was assessed using the forward and backward digit span tasks from the Figure 2. Morphological patterns of ACC. The two ACC sulcal patterns: “single” type, with only the cingulate sulcus, and “double parallel” WISC-IV (Wechsler, 2003). In these two working memory type, with an additional PCS. ACC sulci (blue) are represented on tasks, the children listened to a series of discrete digits the cortical surface (gray/white interface). and subsequently recalled the series of digits in the same

98 Journal of Cognitive Neuroscience Volume 26, Number 1 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021 (i.e., forward digit span task) or reverse (i.e., backward the occurrence and extent of local sulci (e.g., Leonard, digit span task) order of presentation. In each task, the Towler, Welcome, & Chiarello, 2009; Huster, Westerhausen, children first performed two series of two digits. The series Kreuder, Schweiger, & Wittling, 2007; Fornito et al., 2004; of digits were subsequently increased by one digit every Yucel et al., 2001). ACC sulcal pattern was classified as two trials. The task was terminated when a child failed “single” or “double parallel” type (Ono et al., 1990) based to recall two consecutive series with the same number of on the presence or absence of a PCS (Figure 2). This digits. The working memory span (or score) was defined 3-D approach was used to overcome methodological as the number of correctly recalled digits in the last series. issues inherent to the analysis of the sulcal pattern of The forward and backward digit span tasks were used to ACC from the two-dimensional sagittal slices. The PCS Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021 assess the ability to maintain (i.e., forward digit span task) was defined as the sulcus located dorsal to the cingulate or maintain and manipulate information (i.e., backward sulcus with a course clearly parallel to the cingulate digit span task), respectively, in verbal working memory. sulcus (Yucel et al., 2001; Paus et al., 1996). To reduce In addition, children performed a battery of nonexecu- the ambiguity from the confluence of the PCS and the tive tasks: three Piagetian logicomathematical tasks (i.e., cingulate sulcus with the superior rostral sulcus (Paus the number conservation task, the substance conservation et al., 1996), we determined the anterior limit of the task, and the class inclusion task), a numerical task (i.e., PCS as the point at which the sulcus extends posteriorly the number estimation line task), and a visual task (i.e., from an imaginary vertical line running perpendicular Navonʼslocal–global task). Therefore, childrenʼsperfor- to the line passing through the anterior and posterior mance on these tasks were not analyzed in this study. commissures (AC–PC) and parallel to the anterior com- missure (Huster et al., 2007; Yucel et al., 2001). The PCS was considered absent if there were no clearly devel- MRI Acquisition oped horizontal sulcus elements parallel to the cingulate We acquired anatomical MRI from the Cyceron biomedical sulcus and extending at least 20 mm (interruptions imaging platform (Caen, France, www.cyceron.fr) on or gaps in the PCS course was not taken into account a 3T MRI scanner (Achieva, Philips Medical System, The for the length measure). The finer distinction between Netherlands), using 3-D T1-weighted spoiled gradi- “present” and “prominent” PCS (Yucel et al., 2001; Paus ent images (field of view = 256 mm, slice thickness = et al., 1996), leading to three ACC sulcal pattern types, 1.33 mm, 128 slices, matrix size = 192 × 192 voxels). was not used here because this distinction is based on To reduce motion, provide a positive experience, and the PCS length of adult —that is, greater than decrease wait times, we obtained MRIs as the children 20 mm according to Pausʼs classification (Paus et al., passively watched a cartoon on an MRI-compatible screen 1996) or greater than 40 mm according to Yucelʼsclassi- (Lemaire, Moran, & Swan, 2009). fication (Yucel et al., 2001) for a prominent PCS (Leonard et al., 2009). Furthermore, the classification of ACC mor- phology into five categories by grouping the individual MRI Analysis measurements of PCS in 15-mm steps was also proposed An automated preprocessing step skull-stripped T1 MRIs (Huster et al., 2007). However, the present/prominent or and segmented the brain tissues. No spatial normalization five categories of ACC sulcal pattern cannot be applied was applied to MRIs to overcome potential bias that may to characterize ACC sulcal pattern of developing brains, result from the sulcus shape deformations induced by as brain size and PCS length increase with age. Notably, the warping process. The cortical folds were automatically the binary classification of ACC sulcal pattern (“single”/ segmented throughout the cortex from the skeleton of “double parallel” type)usedinourstudywaspreviously the gray matter/cerebrospinal fluid mask, with the cortical used in a study on schizophrenia (Fornito, Yucel, et al., folds corresponding to the crevasse bottoms of the 2006). “landscape,” the altitude of which is defined by its intensity on the MRIs. This definition provides a stable and robust Statistical Analysis sulcal surface definition that is not affected by variations in cortical thickness or gray matter/white matter contrast We conducted separately 2 (ACC Sulcal Pattern, i.e., (Mangin et al., 2004). For each participant, images at each “symmetric” vs. “asymmetric”) × 2 (Stroop Condition, processing step were visually checked. No segmentation i.e., “conflict” vs. “no-conflict”) mixed-design ANOVAs error was detected. Image analysis was performed with on the RTs and ERs of the Stroop task. In addition, we the Morphologist toolbox using BrainVISA 4.2 software ran a 2 (ACC Sulcal Pattern, i.e., “symmetric” vs. “asym- (brainvisa.info). metric”) × 2 (Working Memory Task, i.e., “forward” vs. “backward”) mixed-design ANOVA on the scores in the forward and backward digit span tasks. When we ACC Classification compared two means, we computed two-tailed t tests The sulcal pattern of ACC was visually assessed using 3-D, or Welchʼs t tests in cases of unequal variances. For each mesh-based reconstruction of cortical folds to measure analysis, we reported the effect size either in the ANOVA

Cachia et al. 99 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021 Figure 3. Interindividual variability of ACC sulcal pattern. Superimposition of the 3-D mesh-based reconstructions of the cingulate sulcus (turquoise) and PCS (blue) for all children included in the study. Sulci were represented on the cortical surface (gray/white

interface). The reconstructions Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021 of the sulci of each child were linearly aligned in a common referential (MNI space) for visualization purpose.

(partial η2) or in terms of the difference of the means p = .26. Finally, the difference in RTs between the conflict (Cohenʼs d). and the no-conflict conditions was greater for children with symmetric ACC sulcal pattern (74.2 ± 31.8 sec vs. 37.3 ± 10.8 sec) than for children with asymmetric ACC sulcal RESULTS pattern (52.5 ± 17.6 sec vs. 37.7 ± 10.8 sec) as witnessed Participants were divided into two groups based on the by a significant two-way interaction, F(1, 17) = 5.87, p < 2 asymmetry of the sulcal pattern of ACC: 11 children with .025, ηp = .26. Critically, the Stroop interference scores symmetrical ACC sulcal pattern—“single” (n =9)or (i.e., RT difference between the conflict and no-conflict “double parallel” (n = 2) type in both hemispheres— conditions) were lower; thus, CC efficiency was higher in and 8 children with asymmetrical ACC sulcal pattern— children with asymmetrical ACC (14.9 ± 13.2 sec) than in “single” type in the left hemisphere and “double parallel” children with symmetrical ACC (36.8 ± 22.9 sec), Welch-t type in the right hemisphere (n = 4) or vice versa (n = (16.32) = 2.64, p < .025, d = 1.17 (Figure 4). ACC asym- 4; see Figure 3 for the interindividual variability of ACC metry explained 21% of Stroop interference score variabil- sulcal pattern). These groups were matched for age, sex, ity based on RTs. Finally, we note that children in the household income as a proxy indicator for socioeconomic two groups required the same amount of time to name status, scores on the Edinburgh Handedness Inventory the animal body in the no-conflict condition (37.3 sec vs. (Oldfield, 1971), and raw scores on the colored progres- 37.7 sec), t(17) = .06, p = .95 (see Table 2). sive matrices of Raven as a proxy indicator for general A two-way mixed-design ANOVA on the ERs demon- intelligence (Raven, Raven, & Court, 1976; see Table 1). strated a similar pattern of results. Children had more The two-way mixed-design ANOVA in the RTs demon- errors in the conflict (8.1 ± 4.7%) than in the no-conflict strated that, irrespective of ACC sulcal pattern, children conditions (3.5 ± 3.7%), F(1, 17) = 22.37, p < .0001, 2 needed more time to name the animalsʼ bodies in the ηp = .57; the sulcal pattern of ACC had no main effect conflict (65.1 ± 28.3 sec) than in the no-conflict (37.5 ± on the ERs, F < 1. Finally, similar to the findings for the 2 10.5 sec) conditions, F(1, 17) = 32.57, p < .0001, ηp = RTs,thedifferenceinERsbetweentheconflictandthe .66, revealing a classical Stroop-like interference effect on no-conflict conditions was greater for children with the RTs. Furthermore, we found no main effect of ACC symmetric ACC sulcal pattern (8.7 ± 4.4% vs. 2.3 ± 3.9%) Sulcal Pattern—that is, RTs averaged over the Stroop con- than for children with asymmetric ACC sulcal pattern ditions did not differ between children with symmetric (7.3 ± 5.3% vs. 5.2 ± 2.9%), as demonstrated by a significant 2 ACC and children with asymmetric ACC, F(1, 17) = 1.67, two-way interaction, F(1, 17) = 5.84, p <.025,ηp = .26.

Table 1. Demographic Characteristics of the Sample of Preschoolers (n = 19)

Sym. n = 11 Asym. n = 8 Welch-t/χ2 p Age (years) 5.48 (0.2) 5.47 (0.15) t =0.10 .91 Sex (female/male) 5/6 5/3 χ2 =0.12 .73 Household (low/high income) 5/6 6/2 χ2 =1.66 .19 Handedness (Oldfield score) 91.9 (26.8) 94.4 (15.7) t = .025 .80 Raven (raw score) 27.9 (3.2) 29.3 (1.1) t = .087 .40

100 Journal of Cognitive Neuroscience Volume 26, Number 1 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021 Figure 4. Asymmetry of ACC and cognitive control efficiency in preschoolers (n = 19). Average Stroop interference scores (RTs and ERs) in preschoolers with symmetrical ACC (“single” type or “double parallel” type in both hemispheres; light

gray; n = 11) or asymmetrical Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021 ACC (“single” type in the left hemisphere and “double parallel” type in the right hemisphere or vice versa; hashed; n = 8). Error bars denote SEM.

Consistent with the results reported on the RTs, the Stroop tern of ACC. As for the RTs, children with asymmetrical interference scores computed on the ERs were lower in (5.2 ± 2.9%) and symmetrical (2.3 ± 3.9%) sulcal pattern children with asymmetrical ACC sulcal pattern (2.1 ± of ACC committed approximately the same number of 3.9%) than in children with symmetrical ACC sulcal pattern errors in the no-conflict condition, t(17) = 1.79, p = .09. (6.4 ± 3.9%), Welch-t (15.32) = 2.42, p <.05,d =1.1.As A 2 (ACC Sulcal Pattern, i.e., symmetric vs. asymmetric) × for the RTs, 21% of the variance of the Stroop interference 2 (Working Memory Task, i.e., forward vs. backward) mixed- score computed on the ERs is explained by the sulcal pat- design ANOVA revealed that irrespective of ACC sulcal pattern, the scores in the backward digit span tasks were smaller (M = 2.32 ± .58) than those obtained in the forward Table 2. Mean (M) and Standard Deviation (SD) of the RTs (M = 3.79 ± .92) digit span tasks, F(1, 17) = 30.85, p < and ERs in the Stroop Color Word Task for Children with η 2 Symmetrical (Sym.) and Asymmetrical (Asym.) Sulcal Pattern .0001, p = .65. There was no main effect of ACC Sulcal of ACC Pattern on the scores averaged over the two conditions, F < 1. Critically, the differences between the forward Sym. Asym. and backward scores were similar for children with MSDMSDsymmetric (4.09 ± 1.04 vs. 2.18 ± .41) and asymmetric (3.38 ± .52 vs. 2.5 ± .76) ACC patterns, as the lack of sig- RTs (sec) nificant two-way interactions suggests, F(1, 17) = 4.26, No conflict 37.3 10.8 37.6 10.7 p = .06. Moreover, planned comparisons revealed that the scores did not differ between the children with sym- Conflict 74.2 31.8 52.5 17.6 metric and asymmetric ACC sulcal patterns in the for- Stroop score 36.8 22.9 14.9 13.4 ward, t(17) = 1.77, p = .09, and backward, t(17) = 1.19, p = .25, digit span tasks. ERs (%) No conflict 2.3 3.9 5.2 2.9 DISCUSSION Conflict 8.7 4.4 7.3 5.3 As expected, children with an asymmetrical sulcal pat- Stroop score 6.4 3.9 2.1 3.9 tern of ACC are less sensitive to the interference in a

Cachia et al. 101 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021 Stroop-like task than children with a symmetrical sulcal robust to changes induced by maturation after birth pattern of ACC. Thus, preschoolersʼ CC efficiency includ- and experience-dependent factors (Sun et al., 2012). The ing inhibitory control—that is, the ability to overcome a sulcal pattern results from early neurodevelopmental cognitive conflict and inhibit a dominant response—is processes, starting as early as 10 weeks of fetal life, that directly related to their ACC sulcal pattern. Critically, shape the cortex anatomy from a smooth lissencephalic the effect of the sulcal pattern of ACC on the Stroop structure to a highly convoluted surface (Welker, 1988). interference score unlikely results from a difference in In particular, the development of ACC sulcal pattern the ability to name the animals, given that we found no occurs between 10 and 15 weeks of fetal life (Feess- difference in the no-conflict condition between the two Higgins & Larroche, 1987; Chi, Dooling, & Gilles, 1977). Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021 groups. Furthermore, we note that analyses of the RTs Such long-term effect of early neurodevelopmental and ERs revealed a similar pattern of results, with strong constraints on the subsequent development of cognitive effect sizes providing evidence (a) of the robustness of capacities is in line with previous studies in adults showing the behavioral effects of ACC sulcal pattern, despite the that variations in ACC sulcal patterns are related to indi- sample size, and (b) the lack of speed accuracy trade-off. vidual differences in CC efficiency (Huster et al., 2009; Moreover, ACC sulcal pattern had no effect on perfor- Fornito et al., 2004) as well as in four core temperament mances in the forward and backward digit span tasks. dimensions, that is, effortful control, negative affectivity, Taken together, the results suggest that ACC sulcal pat- surgency, and affiliation (Whittle et al., 2009). An impor- tern contributes to the ability to resolve conflicts (i.e., tant contribution of our findings is that such long-term as in the Animal Stroop task) but did not contribute to effect was observed for the first time in preschoolers, the ability to maintain and manipulate information in namely in the early stages of cognitive and neural devel- verbal working memory (i.e., as in the forward and the opment. However, because of the sample size, we could backward digit span tasks) or manage the increasing dif- not statistically determine whether children with a left- ficulty of a task (i.e., the difference between the scores ward asymmetry of the sulcal pattern of ACC (i.e., PCS in the backward and the forward digit span tasks). A in the left but not in the right hemispheres) have greater potential limitation of this study is the small sample size, CC efficiency than children with a rightward asymmetry reflecting the difficulty to conduct brain imaging studies (i.e., PCS in the left but not in the right hemispheres) as in young children. in adults (Huster et al., 2009; Whittle et al., 2009; Fornito This study focuses on the general construct of execu- et al., 2004).1 tive functions and the inhibition of prepotent responses; Several factors contribute to the neurodevelopmental therefore, our findings do not provide information on processes that influence the shape of the folded cerebral the specific cognitive processes affected by ACC sulcal cortex (Mangin, Jouvent, & Cachia, 2010), including struc- pattern. Indeed, although ACC is consistently activated tural connectivity through axonal tension forces (Hilgetag in the Stroop task (Roberts & Hall, 2008; Nee, Wager, & & Barbas, 2006; Van Essen, 1997). These mechanical Jonides, 2007), the precise role of this region remains constraints lead to a compact layout that optimizes the elusive (Botvinick, Cohen, & Carter, 2004; MacLeod & transmission of neuronal signals between brain regions MacDonald, 2000). ACC is critical for monitoring conflicts (Klyachko & Stevens, 2003) and thus brain network func- (Kerns et al., 2004; Botvinick et al., 2001; Carter et al., tioning. In this context, we speculate that the differences 2000), selecting responses in underdetermined contexts in CC efficiency observed in preschoolers with symmetrical (Palmer et al., 2001), detecting errors (Braver, Barch, Gray, or asymmetrical ACC might reflect differences in brain Molfese, & Snyder, 2001; Falkenstein, Hoormann, Christ, network efficiency because of differences in long-range & Hohnsbein, 2000; Carter et al., 1998), making reward- (i.e., interhemispheric) and short-range (i.e., intrahemi- based decisions (Nieuwenhuis, Yeung, Holroyd, Schurger, spheric) brain connectivity. Increased cognitive efficiency & Cohen, 2004; Bush et al., 2002), and encoding cogni- in asymmetric brains might be associated with hemispheric tive efforts (Rushworth, Walton, Kennerley, & Bannerman, specialization, as it is more efficient to transfer informa- 2004; Botvinick et al., 2001). Additional studies are needed tion between close areas within the same hemisphere to determine the precise cognitive process affected by rather than between distant areas distributed in the two the morphology of ACC, which in turn might shed light hemispheres (Deary, Penke, & Johnson, 2010; Toga & on the cognitive processes critical to perform the Animal Thompson, 2003). The association between hemispheric Stroop task and the role of ACC in supporting these pro- specialization and the asymmetry of the brain morphology cesses. For instance, future researches should study the is supported by studies of the corpus callosum, a large effect of ACC sulcal pattern on the performance in differ- bundle of interhemispheric fibers, showing that asym- ent executive tasks tackling different types of executive metrical brains have fewer and/or thinner fibers connecting processes. the two hemispheres relative to more symmetrical brain, Thus, our results support the hypothesis that CC as evidenced by a reduced midsagittal area (Witelson, efficiency in preschoolers is rooted in early neurodevel- 1985) and microstructural integrity measured using dif- opmental processes. The cortical folding patterns are fusion MRI (Putnam, Wig, Grafton, Kelley, & Gazzaniga, primarily determined in utero (Welker, 1988) and are 2008). Individuals with no corpus callosum (i.e., complete

102 Journal of Cognitive Neuroscience Volume 26, Number 1 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021 agenesis) exhibit an intact Stroop interference effect ultimately contribute to shape specific educational inter- (Brown, Thrasher, & Paul, 2001), suggesting that the pro- ventions designed to help children overcome their CC cesses involved in performing the Stroop task are highly deficits, particularly those with symmetrical sulcal pattern lateralized in the brain. If these processes are lateralized, of ACC who are at increased risk of developing faulty CC then it is reasonable to expect that morphological asym- efficiency. metry in the regions involved in performing the Stroop In conclusion, this study provides the first evidence task, such as ACC, would produce better efficiency by that preschoolersʼ CC efficiency is likely associated with reinforcing hemispheric specialization. This hypothesis is ACC sulcal pattern, thereby suggesting that the brain supported by multimodal brain imaging of the cortex shape could result in early constraints on human executive Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021 morphology and the white matter connectivity in the ability. same individuals, revealing that participants with different sulcal patterns have distinct short-range white matter con- nectivity (Leonard, Eckert, & Kuldau, 2006). Therefore, Acknowledgments the increased CC efficiency observed in children with We thank the CNRS for financial support and the French Board asymmetric ACC in our study might reflect the asymmetry of Education for their collaboration. of the underlying white matter connectivity of ACC. Reprint requests should be sent to Arnaud Cachia, Laboratory Faulty executive functions including CC can account for for the Psychology of Child Development and Education, CNRS learning difficulties in children, such as errors, reasoning U3521, Paris-Descartes University, Alliance for Higher Education biases, and maladjustment, both in cognitive (Borst, Poirel, and Research Sorbonne Paris Cité, Sorbonne, 46 rue Saint-Jacques, 75005 Paris, France, or via e-mail: [email protected]. Pineau, Cassotti, & Houdé, 2013; Poirel et al., 2012; Houdé, 2000) and social (Steinberg, 2005) domains. Childrenʼs executive function efficiency actually predicts, for in- Note stance, health and professional success later in life (Moffitt etal.,2011).Thepredictivenatureofchildrenʼsexecutive 1. That said, the pattern of Stroop interference scores suggests that children with leftward asymmetry (13.1 ± 17.4; n = 4) could functions including CC efficiency on cognitive and social have greater CC efficiency than children with rightward asym- development may be partly related to the early neuro- metry (16.7 ± 9.7; n = 4), children with PCS in both hemi- developmental constraints induced by the sulcal pattern spheres (24.9 ± 11.5; n =2),andchildrenwithnoPCS(39.5± of ACC (Dubois et al., 2008). 24.4; n =9). However, brain–behavior associations are not fixed in all cases. For instance, previous studies reported that CC efficiency, assessed either in a visual discrimination task REFERENCES (Casey et al., 1997) or in a Flanker task (Fjell et al., 2012), is related to the cortical surface area of ACC (Fjell et al., Amiez, C., Neveu, R., Warrot, D., Petrides, M., Knoblauch, K., 2012; Casey et al., 1997). Critically, the relationship is & Procyk, E. (2013). The location of feedback-related activity in the midcingulate cortex is predicted by local stronger for younger children (under 12 years old) and morphology. Journal of Neuroscience, 33, 2217–2228. decreases linearly with age (Fjell et al., 2012). Because Armstrong, E., Schleicher, A., Omran, H., Curtis, M., & the cortical surface area of ACC is determined in part Zilles, K. (1995). The ontogeny of human gyrification. by ACC sulcal pattern (Fornito et al., 2008; Fornito, Whittle, Cerebral Cortex, 5, 56–63. et al., 2006), the relationship between ACC sulcal pattern Baddeley, A. (2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4, and the CC efficiency reported in our study might vary 829–839. with age. Hence, early neuroanatomical constraints might Barkovich, A. J., Guerrini, R., Kuzniecky, R. I., Jackson, G. D., be overcome during cognitive development by training & Dobyns, W. B. (2012). A developmental and genetic CC. Indeed, CC continues to mature from childhood to classification for malformations of cortical development: – adolescence (Luna, 2009; Luna, Garver, Urban, Lazar, & Update 2012. Brain, 135, 1348 1369. Blair, C., & Razza, R. P. (2007). Relating effortful control, Sweeney, 2004) and can be modified by training and executive function, and false belief understanding to practice (Diamond, 2013). emerging math and literacy ability in kindergarten. Longitudinal studies in large-scale samples should Child Development, 78, 647–663. investigate the possible interactions between the sulcal Borst, G., Poirel, N., Pineau, A., Cassotti, M., & Houdé, O. pattern of ACC and intense preschool interventions that (2013). Inhibitory control efficiency in a Piaget-like class-inclusion task in school-age children and adults: have shown to improve executive functions including A developmental negative priming study. Developmental CC efficiency (Diamond et al., 2007). An early objective Psychology, 49, 1366–1374. assessment of CC in children is critical, given that (a) Botvinick, M. M. (2007). Conflict monitoring and decision executive function training is more beneficial for children making: Reconciling two perspectives on anterior cingulate with faulty executive function efficiency (Diamond et al., function. Cognitive, Affective, & , 7, 356–366. 2007) and (b) executive functions can demonstrate im- Botvinick, M. M., Braver, T. S., Barch, D. M., Carter, C. S., proved results in children as early as 4 or 5 years (Moffitt & Cohen, J. D. (2001). Conflict monitoring and cognitive et al., 2011). Hence, our brain-imaging findings may control. Psychological Review, 108, 624–652.

Cachia et al. 103 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021 Botvinick, M. M., Cohen, J. D., & Carter, C. S. (2004). Conflict Duckworth, A. L., & Seligman, M. E. (2005). Self-discipline monitoring and anterior cingulate cortex: An update. outdoes IQ in predicting academic performance of Trends in Cognitive Sciences, 8, 539–546. adolescents. Psychological Science, 16, 939–944. Braver, T. S., Barch, D. M., Gray, J. R., Molfese, D. L., & Egner, T., & Hirsch, J. (2005). Cognitive control mechanisms Snyder, A. (2001). Anterior cingulate cortex and response resolve conflict through cortical amplification of task-relevant conflict: Effects of frequency, inhibition and errors. information. Nature Neuroscience, 8, 1784–1790. Cerebral Cortex, 11, 825–836. Falkenstein, M., Hoormann, J., Christ, S., & Hohnsbein, J. Brown, W. S., Thrasher, E. D., & Paul, L. K. (2001). (2000). ERP components on reaction errors and their Interhemispheric Stroop effects in partial and complete functional significance: A tutorial. Biological Psychology, – agenesis of the corpus callosum. Journal of the 51, 87 107. Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021 International Neuropsychological Society, 7, 302–311. Feess-Higgins, A., & Larroche, J. (1987). Development of the Bush, G., Luu, P., & Posner, M. I. (2000). Cognitive and human foetal brain. An anatomical atlas. Paris: Masson. emotional influences in anterior cingulate cortex. Fjell, A. M., Walhovd, K. B., Brown, T. T., Kuperman, J. M., Trends in Cognitive Sciences, 4, 215–222. Chung, Y., Hagler, D. J., Jr., et al. (2012). Multimodal imaging Bush, G., Vogt, B. A., Holmes, J., Dale, A. M., Greve, D., of the self-regulating developing brain. Proceedings of the Jenike, M. A., et al. (2002). Dorsal anterior cingulate cortex: National Academy of Sciences, U.S.A., 109, 19620–19625. A role in reward-based decision making. Proceedings of Flook, L., Smalley, S. L., Kitil, M. J., Galla, B. M., Kaiser- the National Academy of Sciences, U.S.A., 99, 523–528. Greenland, S., Locke, J., et al. (2010). Effects of mindful Carter, C. S., Braver, T. S., Barch, D. M., Botvinick, M. M., Noll, awareness practices on executive functions in elementary D., & Cohen, J. D. (1998). Anterior cingulate cortex, error school children. Journal of Applied , 26, detection, and the online monitoring of performance. 70–95. Science, 280, 747–749. Fornito, A., Whittle, S., Wood, S. J., Velakoulis, D., Pantelis, C., Carter, C. S., Macdonald, A. M., Botvinick, M., Ross, L. L., & Yucel, M. (2006). The influence of sulcal variability on Stenger, V. A., Noll, D., et al. (2000). Parsing executive morphometry of the human anterior cingulate and processes: Strategic vs. evaluative functions of the anterior paracingulate cortex. Neuroimage, 33, 843–854. cingulate cortex. Proceedings of the National Academy Fornito, A., Wood, S. J., Whittle, S., Fuller, J., Adamson, C., of Sciences, U.S.A., 97, 1944–1948. Saling, M. M., et al. (2008). Variability of the paracingulate Casey, B. J., Thomas, K. M., Welsh, T. F., Badgaiyan, R. D., sulcus and morphometry of the medial frontal cortex: Eccard, C. H., Jennings, J. R., et al. (2000). Dissociation of Associations with cortical thickness, surface area, volume, response conflict, attentional selection, and expectancy with and sulcal depth. Mapping, 29, 222–236. functional magnetic resonance imaging. Proceedings of the Fornito, A., Yucel, M., Wood, S. J., Proffitt, T., McGorry, National Academy of Sciences, U.S.A., 97, 8728–8733. P. D., Velakoulis, D., et al. (2006). Morphology of Casey, B. J., Trainor, R., Giedd, J., Vauss, Y., Vaituzis, C. K., the paracingulate sulcus and executive in Hamburger, S., et al. (1997). The role of the anterior schizophrenia. Schizophrenia Research, 88, 192–197. cingulate in automatic and controlled processes: Fornito, A., Yucel, M., Wood, S., Stuart, G. W., Buchanan, A developmental neuroanatomical study. Developmental J. A., Proffitt, T., et al. (2004). Individual differences in Psychobiology, 30, 61–69. anterior cingulate/paracingulate morphology are related Chi, J. G., Dooling, E. C., & Gilles, F. H. (1977). Gyral to executive functions in healthy males. Cerebral Cortex, development of the human brain. Annals of Neurology, 14, 424–431. 1, 86–93. Gathercole, S. E., Pickering, S. J., Ambridge, B., & Wearing, H. Deary, I. J., Penke, L., & Johnson, W. (2010). The neuroscience (2004). The structure of working memory from 4 to 15 years of human intelligence differences. Nature Reviews of age. Developmental Psychology, 40, 177–190. Neuroscience, 11, 201–211. Giedd, J. N., Lalonde, F. M., Celano, M. J., White, S. L., Dehay, C., Giroud, P., Berland, M., Killackey, H., & Kennedy, H. Wallace, G. L., Lee, N. R., et al. (2009). Anatomical brain (1996). Contribution of thalamic input to the specification magnetic resonance imaging of typically developing of cytoarchitectonic cortical fields in the primate: Effects of children and adolescents. Journal of the American bilateral enucleation in the fetal monkey on the boundaries, Academy of Child & Adolescent Psychiatry, 48, 465–470. dimensions, and gyrification of striate and extrastriate cortex. Gogtay, N., Giedd, J. N., Lusk, L., Hayashi, K. M., Greenstein, D., Journal of Comparative Neurology, 367, 70–89. Vaituzis, A. C., et al. (2004). Dynamic mapping of human Diamond, A. (2013). Executive functions. Annual Review of cortical development during childhood through early Psychology, 64, 135–168. adulthood. Proceedings of the National Academy of Diamond, A., Barnett, W. S., Thomas, J., & Munro, S. (2007). Sciences, U.S.A., 101, 8174–8179. Preschool program improves cognitive control. Science, Hilgetag, C. C., & Barbas, H. (2006). Role of mechanical 318, 1387–1388. factors in the morphology of the primate cerebral cortex. Diamond, A., & Lee, K. (2011). Interventions shown to PLOS Computational Biology, 2, e22. aid executive function development in children 4 to Hillman, C. H., Erickson, K. I., & Kramer, A. F. (2008). 12 years old. Science, 333, 959–964. Be smart, your heart: Exercise effects on brain Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., and cognition. Nature Reviews Neuroscience, 9, 58–65. & May, A. (2004). Neuroplasticity: Changes in grey matter Holmes, J., Gathercole, S. E., & Dunning, D. L. (2009). Adaptive induced by training. Nature, 427, 311–312. training leads to sustained enhancement of poor working Draganski, B., Gaser, C., Kempermann, G., Kuhn, H. G., memory in children. Developmental Science, 12, F9–F15. Winkler, J., Buchel, C., et al. (2006). Temporal and spatial Houdé, O. (2000). Inhibition and cognitive development: dynamics of brain structure changes during extensive Object, number, categorization, and reasoning. Cognitive learning. Journal of Neuroscience, 26, 6314–6317. Development, 15, 63–73. Dubois, J., Benders, M., Borradori-Tolsa, C., Cachia, A., Huster, R. J., Enriquez-Geppert, S., Pantev, C., & Bruchmann, M. Lazeyras, F., Ha-Vinh Leuchter, R., et al. (2008). Primary (2012). Variations in midcingulate morphology are related cortical folding in the human newborn: An early marker to ERP indices of cognitive control. Brain Structure of later functional development. Brain, 131, 2028–2041. & Function. Epub ahead of print.

104 Journal of Cognitive Neuroscience Volume 26, Number 1 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021 Huster, R. J., Westerhausen, R., & Herrmann, C. S. (2011). Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, Sex differences in cognitive control are associated with R. J., Harrington, H., et al. (2011). A gradient of childhood midcingulate and callosal morphology. Brain Structure & self-control predicts health, wealth, and public safety. Function, 215, 225–235. Proceedings of the National Academy of Sciences, U.S.A., Huster, R. J., Westerhausen, R., Kreuder, F., Schweiger, E., & 108, 2693–2698. Wittling, W. (2007). Morphologic asymmetry of the human Molko, N., Cachia, A., Riviere, D., Mangin, J. F., Bruandet, M., anterior cingulate cortex. Neuroimage, 34, 888–895. Le Bihan, D., et al. (2003). Functional and structural Huster, R. J., Wolters, C., Wollbrink, A., Schweiger, E., alterations of the intraparietal sulcus in a developmental Wittling, W., Pantev, C., et al. (2009). Effects of anterior dyscalculia of genetic origin. Neuron, 40, 847–858.

cingulate fissurization on cognitive control during Stroop Nee, D. E., Wager, T. D., & Jonides, J. (2007). Interference Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021 interference. Human Brain Mapping, 30, 1279–1289. resolution: Insights from a meta-analysis of neuroimaging Hyde, K. L., Lerch, J., Norton, A., Forgeard, M., Winner, E., tasks. Cognitive, Affective, & Behavioral Neuroscience, 7, Evans, A. C., et al. (2009). Musical training shapes structural 1–17. brain development. Journal of Neuroscience, 29, 3019–3025. Nieuwenhuis, S., Yeung, N., Holroyd, C. B., Schurger, A., Kerns, J. G., Cohen, J. D., MacDonald, A. W., III, Cho, R. Y., & Cohen, J. D. (2004). Sensitivity of electrophysiological Stenger, V. A., & Carter, C. S. (2004). Anterior cingulate activity from medial frontal cortex to utilitarian and conflict monitoring and adjustments in control. Science, performance feedback. Cerebral Cortex, 14, 741–747. 303, 1023–1026. Oldfield, R. C. (1971). The assessment and analysis of Klyachko, V. A., & Stevens, C. F. (2003). Connectivity handedness: The Edinburgh inventory. Neuropsychologia, optimization and the positioning of cortical areas. 9, 97–113. Proceedings of the National Academy of Sciences, Ono, M., Kubik, S., & Abarnathey, C. D. (1990). Atlas of the U.S.A., 100, 7937–7941. cerebral sulci. New York: Thieme. Lakes, K. D., & Hoyt, W. I. (2004). Promoting self-regulation Palmer, E. D., Rosen, H. J., Ojemann, J. G., Buckner, R. L., through school-based martial arts training. Journal of Kelley, W. M., & Petersen, S. E. (2001). An event-related Applied Developmental Psychology, 25, 283–302. fMRI study of overt and covert word stem completion. Lemaire, C., Moran, G. R., & Swan, H. (2009). Impact of Neuroimage, 14, 182–193. audio/visual systems on pediatric sedation in magnetic Pardo, J. V., Pardo, P. J., Janer, K. W., & Raichle, M. E. (1990). resonance imaging. Journal of Magnetic Resonance The anterior cingulate cortex mediates processing selection Imaging, 30, 649–655. in the Stroop attentional conflict paradigm. Proceedings of Leonard, C. M., Eckert, M. A., & Kuldau, J. M. (2006). Exploiting the National Academy of Sciences, U.S.A., 87, 256–259. human anatomical variability as a link between genome Paus, T., Tomaiuolo, F., Otaky, N., MacDonald, D., Petrides, M., and cognome. Genes, Brain and Behavior, 5(Suppl. 1), Atlas, J., et al. (1996). Human cingulate and paracingulate 64–77. sulci: Pattern, variability, asymmetry, and probabilistic Leonard, C. M., Towler, S., Welcome, S., & Chiarello, C. (2009). map. Cerebral Cortex, 6, 207–214. Paracingulate asymmetry in anterior and midcingulate Petersen, S. E., & Posner, M. I. (2012). The attention system cortex: Sex differences and the effect of measurement of the human brain: 20 Years after. Annual Review of technique. Brain Structure & Function, 213, 553–569. Neuroscience. doi: 10.1146/annurev-neuro062111-150525. Luna, B. (2009). Developmental changes in cognitive control Poirel, N., Borst, G., Simon, G., Rossi, S., Cassotti, M., Pineau, A., through adolescence. Advances in Child Development et al. (2012). Number conservation is related to childrenʼs and Behavior, 37, 233–278. prefrontal inhibitory control: An fMRI study of a Piagetian Luna, B., Garver, K. E., Urban, T. A., Lazar, N. A., & Sweeney, task. PLoS One, 7:e40802. J. A. (2004). Maturation of cognitive processes from late Putnam, M. C., Wig, G. S., Grafton, S. T., Kelley, W. M., & childhood to adulthood. Child Development, 75, 1357–1372. Gazzaniga, M. S. (2008). Structural organization of the Mackey, A. P., Hill, S. S., Stone, S. I., & Bunge, S. A. (2011). corpus callosum predicts the extent and impact of cortical Differential effects of reasoning and speed training in activity in the nondominant hemisphere. Journal of children. Developmental Science, 14, 582–590. Neuroscience, 28, 2912–2918. MacLeod, C. M. (1991). Half a century of research on the Rakic, P. (2004). Neuroscience. Genetic control of cortical : An integrative review. Psychological Bulletin, convolutions. Science, 303, 1983–1984. 109, 163–203. Raven, J., Raven, J. C., & Court, J. H. (1998). Manual for Ravenʼs MacLeod, C. M., Dodd, M. D., Sheard, E. D., Wilson, D. E., & progressive matrices and vocabulary scales. Section 2: Bibi, U. (2003). In opposition to inhibition. In B. H. Ross The coloured progressive matrices. San Antonio, Texas: (Ed.), The psychology of learning and motivation (Vol. 43, Harcourt Assessment. pp. 163–214). San Diego, CA: Academic Press. Roberts, K. L., & Hall, D. A. (2008). Examining a supramodal MacLeod, C. M., & MacDonald, P. A. (2000). Interdimensional network for conflict processing: A systematic review and interference in the Stroop effect: Uncovering the cognitive novel functional magnetic resonance imaging data for and neural anatomy of attention. Trends in Cognitive related visual and auditory Stroop tasks. Journal of Sciences, 4, 383–391. Cognitive Neuroscience, 20, 1063–1078. Mangin, J. F., Jouvent, E., & Cachia, A. (2010). In-vivo Rueda, M. R., Rothbart, M. K., McCandliss, B. D., Saccomanno, L., measurement of cortical morphology: Means and meanings. & Posner, M. I. (2005). Training, maturation, and genetic Current Opinion in Neurology, 23, 359–367. influences on the development of executive attention. Mangin, J. F., Riviere, D., Cachia, A., Duchesnay, E., Cointepas, Y., Proceedings of the National Academy of Sciences, U.S.A., Papadopoulos-Orfanos, D., et al. (2004). A framework to 102, 14931–14936. study the cortical folding patterns. Neuroimage, 23(Suppl. 1), Rushworth, M. F., Walton, M. E., Kennerley, S. W., & S129–S138. Bannerman, D. M. (2004). Action sets and decisions in Matthews, S. C., Paulus, M. P., Simmons, A. N., Nelesen, R. A., the medial frontal cortex. Trends in Cognitive Sciences, & Dimsdale, J. E. (2004). Functional subdivisions within 8, 410–417. anterior cingulate cortex and their relationship to autonomic Steinberg, L. (2005). Cognitive and affective development nervous system function. Neuroimage, 22, 1151–1156. in adolescence. Trends in Cognitive Sciences, 9, 69–74.

Cachia et al. 105 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021 Stroop, J. R. (1935). Studies of interference in serial verbal and attentional networks as measured by the attention reactions. Journal of , 18, 643–662. network test. Cerebral Cortex, 21, 345–356. Sun, Z. Y., Kloppel, S., Riviere, D., Perrot, M., Frackowiak, R., White, T., Su, S., Schmidt, M., Kao, C. Y., & Sapiro, G. Siebner, H., et al. (2012). The effect of handedness on the (2010). The development of gyrification in childhood shape of the central sulcus. Neuroimage, 60, 332–339. and adolescence. Brain and Cognition, 72, 36–45. Takeuchi, H., Taki, Y., Sassa, Y., Hashizume, H., Sekiguchi, A., Whittle, S., Allen, N. B., Fornito, A., Lubman, D. I., Simmons, Nagase, T., et al. (2012). Regional gray and white matter J. G., Pantelis, C., et al. (2009). Variations in cortical volume associated with Stroop interference: Evidence from folding patterns are related to individual differences voxel-based morphometry. Neuroimage, 59, 2899–2907. in temperament. Psychiatry Research, 172, 68–74.

Toga, A. W., & Thompson, P. M. (2003). Mapping brain Witelson, S. F. (1985). The brain connection: The corpus Downloaded from http://mitprc.silverchair.com/jocn/article-pdf/26/1/96/1780446/jocn_a_00459.pdf by MIT Libraries user on 17 May 2021 asymmetry. Nature Reviews Neuroscience, 4, 37–48. callosum is larger in left-handers. Science, 229, 665–668. Van Essen, D. C. (1997). A tension-based theory of Wright, I., Waterman, M., Prescott, H., & Murdoch-Eaton, D. morphogenesis and compact wiring in the central (2003). A new Stroop-like measure of inhibitory function nervous system. Nature, 385, 313–318. development: Typical developmental trends. Journal of Vogt, B. (2009). Cingulate neurobiology and disease. Child Psychology and Psychiatry, 44, 561–575. Oxford: Oxford University Press. Yucel, M., Stuart, G. W., Maruff, P., Velakoulis, D., Crowe, S. F., Wechsler, D. (2003). Wechsler Intelligence Scale for Savage, G., et al. (2001). Hemispheric and gender-related Children-Fourth Edition. Administration and scoring differences in the gross morphology of the anterior manual. San Antonio, TX: Harcourt Assessment, Inc. cingulate/paracingulate cortex in normal volunteers: Welker, W. (1988). Why does cerebral cortex fissure and An MRI morphometric study. Cerebral Cortex, 11, 17–25. fold? Cerebral Cortex, 8B, 3–135. Zilles, K., Palomero-Gallagher, N., & Amunts, K. (2013). Westlye, L. T., Grydeland, H., Walhovd, K. B., & Fjell, A. M. Development of cortical folding during evolution and (2011). Associations between regional cortical thickness ontogeny. Trends in Neurosciences, 36, 275–284.

106 Journal of Cognitive Neuroscience Volume 26, Number 1 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/jocn_a_00459 by guest on 28 September 2021